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Disturbance Regimes and Life-History Evolution vol. 157, no. 5 the american naturalist may 2001 Disturbance Regimes and Life-History Evolution David A. Lytle* Department of Entomology and Field of Ecology & Evolutionary 1961; MacArthur and Levins 1967; Huston 1979; Chesson Biology, Cornell University, Ithaca, New York 14853 1994; Lavorel and Chesson 1995), eliminate nonnative taxa (Meffe 1984; Minckley and Meffe 1987; Closs and Lake Submitted June 14, 2000; Accepted December 26, 2000 1996), facilitate invasive taxa (McEvoy et al. 1993), and alter community food web structure (Wootton 1998). Al- though it seems reasonable that strong ecological forces acting within populations could influence the evolution of abstract: Disturbance regimes are ecologically important, but life-history strategies or morphologies, variation in dis- many of their evolutionary consequences are poorly understood. A turbance timing, predictability, frequency, and severity can model is developed here that combines the within- and among- season dynamics of disturbances with evolutionary life-history the- make it difficult to predict the sign and strength of selec- ory. “Disturbance regime” is defined in terms of disturbance timing, tion. Several studies (Harper 1977; Lacey et al. 1983; Ven- frequency, predictability, and severity. The model predicts the optimal able and Brown 1988; Turner et al. 1998) have suggested body size and time at which organisms should abandon a distur- that the frequency of disturbances relative to an organism’s bance-prone growth habitat by maturing and moving to a distur- life span may be evolutionarily important. While it is in- bance-free, nongrowth habitat. The effects of both coarse-grained tuitive that organisms may not adapt to phenomena that (those affecting the entire population synchronously) and fine- grained disturbances (those occurring in a patch dynamics setting) are unlikely to occur during their life spans (e.g., volca- are explored. Several predictions are congruent with previous theory. noes, large fires, big floods, or storms [Turner et al. 1998]), Infrequent or temporally unpredictable disturbances should have lit- it is not clear how frequently disturbances must recur in tle effect on the evolution of life-history strategies, even though they order to elicit evolutionary responses. may cause high mortality. Similar to seasonal time constraints on From an evolutionary perspective, disturbances can be reproduction, disturbance regimes can synchronize metamorphosis categorized as either fine-grained events that affect only a within a population, resulting in a seasonal decline in body size at portion of the population at a time or coarse-grained maturity. Other model predictions are novel. When disturbances cause high mortality, coarse-grained disturbances have a much events that affect the entire population simultaneously stronger effect on life-history strategies than fine-grained distur- (Iwasa and Levin 1995). Fine-grained disturbances (the bances, suggesting that population structure (relative to the scale of “patch dynamics” perspective of Pickett and White [1985]) disturbance) plays a critical evolutionary role when disturbances are include gap formation in forest canopies (Runkle 2000), severe. When within-population variance in juvenile body size is flash floods (Lytle 2000a), and scouring of marine benthos high, two consecutive seasonal declines in body size at maturity can (Airoldi 2000). Coarse-grained disturbances include inter- occur, the first associated with disturbance regime and the second associated with seasonal time constraints. annual variability in growing season length or annual rain- fall (Philippi 1993; Danforth 1999), as well as disturbances Keywords: body size, timing of metamorphosis, patch dynamics, with large areal coverage, such as hurricanes (Turner et state-dependent strategy, geometric mean fitness, arithmetic mean al. 1998). The spatial scale of a disturbance relative to the fitness. spatial distribution of the population is important because it determines how fitness should be estimated in models While the ecological effects of disturbances have been rel- of life-history evolution. When disturbances occur syn- atively well studied, the evolutionary consequences of dis- chronously over the entire population, as with coarse- turbances are less understood. Ecologically, disturbances grained disturbances, the geometric mean of reproductive can mediate the coexistence of competitors (Hutchinson success over multiple seasons is the correct measure of fitness (Cohen 1966; Gillespie 1977). If the population * Present address: Department of Entomology, University of Arizona, Tucson, occurs across many habitat patches that experience dis- Arizona 85721; e-mail: [email protected]. turbances at different times, as with fine-grained distur- Am. Nat. 2001. Vol. 157, pp. 525–536. ᭧ 2001 by The University of Chicago. bances, and the breeding population consists of individuals 0003-0147/2001/15705-0005$03.00. All rights reserved. pooled from these patches, the arithmetic mean is appro- 526 The American Naturalist priate. Thus, evolutionary models incorporating fine- and size at and timing of maturity? How frequently and pre- coarse-grained disturbances are inherently different. In dictably must disturbances recur to affect the evolution of practice, models can sometimes be modified to account these traits? How does population structure influence the for one case or the other (Iwasa and Levin 1995; see evolutionary response to disturbance? Used in this way, below). this disturbance model may be useful for determining Much of the theory concerning how disturbances affect when ecologically important disturbance regimes also have life-history evolution has focused on coarse-grained dis- evolutionary consequences. turbances. Building on the theory of Cohen (1966, 1970, 1971), models have been developed to explore how re- Disturbance Model sources in plants are allotted to growth versus reproduc- tion when the length of the growing season varies across The following model explores how among-season varia- years (King and Roughgarden 1982a, 1982b; Kozłowski bility in disturbance regime (sensu Cohen 1966 and related and Weigert 1986, 1987). For organisms that produce dia- papers) and within-season disturbance dynamics (based pausing seeds or eggs, bet-hedging models predict that on Ludwig and Rowe 1990; Rowe and Ludwig 1991) affect among-year environmental variability may favor repro- life-history evolution. In this model, disturbances affect ductive strategies where only a fraction of offspring ger- individual fitness directly via mortality and indirectly by minate or hatch in a given season (Venable and Lawlor causing mortality in offspring. The model is based on the 1980; Ellner 1985a, 1985b; Bradford and Roff 1993, 1997; following life cycle: juveniles grow in a particular habitat Sasaki and Ellner 1995). In each of these models, the “dis- where they risk mortality from disturbances; at time T, turbance” is the occurrence of an unfavorable physical juveniles stop growing and begin metamorphosis for a environment in a particular year, and the life-history strat- fixed time period; at time TE, nongrowing adults move to egy that maximizes the geometric mean of reproductive a second habitat that is free from disturbance; at time TR, output over many years has the highest fitness. The dis- adults reproduce by placing offspring back in the disturbed turbance does not need to be abiotic, however. Hairston habitat. Thus, juveniles face a trade-off between growth and Munns (1984) used a similar approach to model how and disturbance mortality. Because the risk of disturbance among-year variability in the onset of severe fish predation changes during the season, the model seeks the optimal affected the optimal time for copepods to begin producing body size, W, and time, T, at which juveniles should stop fish-resistant diapausing eggs. growing and mature into the reproductive stage. Most of these coarse-grained models focus on environ- mental variability among years, but many disturbance dy- Disturbances and Survivorship namics occur within years. Relevant parameters include the frequency (expected number of disturbances per sea- The disturbance regime consists of the timing, predicta- son), severity (expected mortality from a single distur- bility, frequency, and severity of disturbances. Survivorship bance), timing (when disturbances occur during a season), is a function of the time spent in this disturbance regime. and predictability (variance in within-season timing) of The probability of an individual surviving i disturbances p Ϫ i disturbances (Pickett and White 1985; Richter et al. 1996). before adulthood isSi (1 l) , where l is the proba- Although seasonal timing and predictability are implicit bility of mortality from a single disturbance event (dis- in many of the coarse-grained models, they assume that turbance severity). Assuming that disturbance events occur only one disturbance occurs per season (frequency p 1 ). independently according to a Poisson distribution, the Some types of disturbance, however, occur multiple times probability of i disturbances occurring from some time t per season or not at all, for example, flash floods (John to adulthood at time TE is 1964; Grimm and Fisher 1989) and the drying and refilling i Ϫu1 of temporary ponds (Semlitsch and Wilber 1988; Newman ue1 P p ,(1) 1989). Thus, a parameter that specifies within-season fre- i i! quency is needed to adequately model these kinds of p ∫TE disturbances. whereu1 t g(t)dt , a time-inhomogeneous
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